Statistics for Analysts: Hypothesis Testing
Run a proper hypothesis test on a real dataset — power analysis, test selection, multiple-comparisons handling.
Python (scipy.stats) or RJupyter / Marimo / Quarto for the notebook
About this project
Most analysts fudge statistics. This project teaches the rigor: pre-registration of the question, power analysis to choose sample size, correct test selection (t-test vs Mann-Whitney vs χ²), and the multiple-comparisons discipline. Pick a real question on a public dataset and run the analysis end-to-end.
Why build this in 2026?
Stats-fluent analysts are protected from AI displacement — defending a confidence interval to a skeptical exec is judgement work.
What you'll ship
- Pre-registered question (written before you looked)
Power analysis with assumptions
Notebook with the full analysis
Plain-English writeup (1-page)
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Skills you'll practice
statisticspythondata analysis